Timothy R. Dafforn

9.9k total citations
152 papers, 7.4k citations indexed

About

Timothy R. Dafforn is a scholar working on Molecular Biology, Cancer Research and Biomedical Engineering. According to data from OpenAlex, Timothy R. Dafforn has authored 152 papers receiving a total of 7.4k indexed citations (citations by other indexed papers that have themselves been cited), including 110 papers in Molecular Biology, 18 papers in Cancer Research and 18 papers in Biomedical Engineering. Recurrent topics in Timothy R. Dafforn's work include Lipid Membrane Structure and Behavior (33 papers), Protein Structure and Dynamics (21 papers) and Protease and Inhibitor Mechanisms (18 papers). Timothy R. Dafforn is often cited by papers focused on Lipid Membrane Structure and Behavior (33 papers), Protein Structure and Dynamics (21 papers) and Protease and Inhibitor Mechanisms (18 papers). Timothy R. Dafforn collaborates with scholars based in United Kingdom, Sweden and Australia. Timothy R. Dafforn's co-authors include Alison Rodger, Timothy J. Knowles, Michael Overduin, David A. Lomas, Corinne J. Smith, Yu-Pin Lin, Ravi Mahadeva, Bengt Nordén, Matthew R. Hicks and Mohammed Jamshad and has published in prestigious journals such as Science, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Timothy R. Dafforn

149 papers receiving 7.3k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Timothy R. Dafforn United Kingdom 50 5.0k 1.0k 1.0k 707 612 152 7.4k
Kevin H. Mayo United States 55 6.0k 1.2× 663 0.6× 656 0.7× 547 0.8× 1.7k 2.7× 283 10.5k
Jan Pieter Abrahams Netherlands 44 6.1k 1.2× 769 0.7× 749 0.7× 361 0.5× 463 0.8× 138 9.3k
Joel P. Mackay Australia 52 7.0k 1.4× 365 0.3× 931 0.9× 367 0.5× 694 1.1× 226 9.9k
David G. Myszka United States 62 9.1k 1.8× 537 0.5× 1.4k 1.3× 430 0.6× 938 1.5× 133 13.2k
Patricia A. Jennings United States 52 6.2k 1.2× 370 0.4× 826 0.8× 499 0.7× 546 0.9× 167 8.3k
David C. Turner United States 42 3.0k 0.6× 429 0.4× 1.1k 1.1× 204 0.3× 616 1.0× 123 5.5k
Karl Harlos United Kingdom 59 5.4k 1.1× 729 0.7× 734 0.7× 270 0.4× 998 1.6× 156 10.5k
Virginia W. Cornish United States 38 7.5k 1.5× 2.7k 2.5× 777 0.8× 319 0.5× 906 1.5× 95 10.9k
Richard W. Kriwacki United States 55 10.6k 2.1× 638 0.6× 1.4k 1.4× 690 1.0× 1.8k 2.9× 130 13.0k
Thomas M. Marti Switzerland 47 3.4k 0.7× 476 0.5× 404 0.4× 802 1.1× 687 1.1× 146 6.9k

Countries citing papers authored by Timothy R. Dafforn

Since Specialization
Citations

This map shows the geographic impact of Timothy R. Dafforn's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Timothy R. Dafforn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Timothy R. Dafforn more than expected).

Fields of papers citing papers by Timothy R. Dafforn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Timothy R. Dafforn. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Timothy R. Dafforn. The network helps show where Timothy R. Dafforn may publish in the future.

Co-authorship network of co-authors of Timothy R. Dafforn

This figure shows the co-authorship network connecting the top 25 collaborators of Timothy R. Dafforn. A scholar is included among the top collaborators of Timothy R. Dafforn based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Timothy R. Dafforn. Timothy R. Dafforn is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Cox, Liam R., Timothy R. Dafforn, Mario Campana, et al.. (2025). Bacterial cell membrane models: choosing the lipid composition. Soft Matter. 21(36). 7054–7073. 2 indexed citations
3.
Rodger, Alison, et al.. (2024). Analysis of the Structure of 14 Therapeutic Antibodies Using Circular Dichroism Spectroscopy. Analytical Chemistry. 9 indexed citations
4.
Li, Huanyu, A.C.W. Pike, Simon R. Bushell, et al.. (2024). Structure and function of the SIT1 proline transporter in complex with the COVID-19 receptor ACE2. Nature Communications. 15(1). 5503–5503. 4 indexed citations
5.
Slater, Alexandre, Sarah C. Lee, Neale Harrison, et al.. (2024). Purification and characterisation of the platelet-activating GPVI/FcRγ complex in SMALPs. Archives of Biochemistry and Biophysics. 754. 109944–109944.
6.
Whalley, Celina, Andrew Bosworth, Andrew D. Beggs, et al.. (2021). Ultrarapid detection of SARS-CoV-2 RNA using a reverse transcription–free exponential amplification reaction, RTF-EXPAR. Proceedings of the National Academy of Sciences. 118(35). 65 indexed citations
7.
Pfukwa, Rueben, et al.. (2021). Linear Dichroism Activity of Chiral Poly(p-Aryltriazole) Foldamers. ACS Omega. 6(48). 33231–33237. 2 indexed citations
8.
Sridhar, Pooja, Patricia C. Edwards, Christopher G. Tate, et al.. (2021). Differences in SMA-like polymer architecture dictate the conformational changes exhibited by the membrane protein rhodopsin encapsulated in lipid nano-particles. Nanoscale. 13(31). 13519–13528. 14 indexed citations
9.
Pfukwa, Rueben, et al.. (2020). Influence of DIBMA Polymer Length on Lipid Nanodisc Formation and Membrane Protein Extraction. Biomacromolecules. 22(2). 763–772. 24 indexed citations
10.
Ali, Aysha, Matthew R. Hicks, D. M. Kenyon, et al.. (2020). Combining bacteriophage engineering and linear dichroism spectroscopy to produce a DNA hybridisation assay. RSC Chemical Biology. 1(5). 449–454. 2 indexed citations
11.
Pollock, Naomi L., Sarah C. Lee, Vijayakumar Balakrishnan, et al.. (2020). Insights on the Quest for the Structure–Function Relationship of the Mitochondrial Pyruvate Carrier. Biology. 9(11). 407–407. 7 indexed citations
12.
Lee, Sarah C., Naomi L. Pollock, Stephen C. L. Hall, et al.. (2019). Analysis of SMALP co-extracted phospholipids shows distinct membrane environments for three classes of bacterial membrane protein. Scientific Reports. 9(1). 1813–1813. 59 indexed citations
13.
Welsh, John H., et al.. (2019). Automated High-Throughput Capillary Circular Dichroism and Intrinsic Fluorescence Spectroscopy for Rapid Determination of Protein Structure. Analytical Chemistry. 91(21). 13794–13802. 18 indexed citations
14.
Hall, Stephen C. L., Gareth J. Price, Bert Klumperman, et al.. (2017). Influence of Poly(styrene-co-maleic acid) Copolymer Structure on the Properties and Self-Assembly of SMALP Nanodiscs. Biomacromolecules. 19(3). 761–772. 58 indexed citations
15.
Laursen, Tomas, Jonas Borch, Camilla Knudsen, et al.. (2016). Characterization of a dynamic metabolon producing the defense compound dhurrin in sorghum. Science. 354(6314). 890–893. 214 indexed citations
16.
Wemyss, Alan M., David J. Smith, Anne Straube, et al.. (2015). Direct detection and measurement of wall shear stress using a filamentous bio-nanoparticle. Nano Research. 8(10). 3307–3315. 6 indexed citations
17.
Jamshad, Mohammed, Timothy J. Knowles, Richard F. Collins, et al.. (2014). Detergent-free purification of ABC (ATP-binding-cassette) transporters. Biochemical Journal. 461(2). 269–278. 155 indexed citations
18.
Dafforn, Timothy R., et al.. (2012). The Mechanics of FtsZ Fibers. Biophysical Journal. 102(4). 731–738. 25 indexed citations
19.
Bromley, Elizabeth H. C., Keith M. Channon, P. J. King, et al.. (2010). Assembly Pathway of a Designed α-Helical Protein Fiber. Biophysical Journal. 98(8). 1668–1676. 45 indexed citations
20.
Dafforn, Timothy R., et al.. (2000). Pathogenic alpha(1)-antitrypsin polymers are formed by reactive loop-beta-sheet A linkage. UCL Discovery (University College London). 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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